/**
 * Context Pressure Utilities
 *
 * Pure functions for context overflow management. These handle:
 * 1. Multi-document detection — counting attached documents in messages
 * 2. Multi-document delegation hint — injected when 3+ documents detected
 * 3. Post-prune context note — injected after pruning/summarization
 *
 * DESIGN PRINCIPLE: The LLM never sees raw token numbers. Context overflow
 * is handled mechanically by pruning (Graph) + auto-continuation (client.js).
 * Only task-driven hints (multi-document) are injected — never budget-based.
 *
 * @see docs/context-overflow-architecture.md
 */
import type { BaseMessage } from '@langchain/core/messages';
/** Result of scanning messages for attached documents */
export interface DocumentDetectionResult {
    /** Total unique documents detected */
    count: number;
    /** Names of detected documents */
    names: string[];
}
/**
 * Scan messages for attached documents using known content patterns.
 *
 * Detects documents from:
 * 1. `# "filename"` headers in "Attached document(s):" blocks (text content)
 * 2. `**filename1, filename2**` in "The user has attached:" blocks (embedded files)
 *
 * @param messages - Conversation messages to scan
 * @returns Document count and names (deduplicated)
 */
export declare function detectDocuments(messages: BaseMessage[]): DocumentDetectionResult;
/**
 * Determine whether the multi-document delegation hint should be injected.
 *
 * Only fires on the first iteration (before any AI response) when the
 * document count meets the threshold. This ensures the agent delegates
 * upfront rather than trying to process all documents itself.
 *
 * @param documentCount - Number of detected documents
 * @param hasAiResponse - Whether the agent has already responded in this chain
 * @returns Whether to inject the delegation hint
 */
export declare function shouldInjectMultiDocHint(documentCount: number, hasAiResponse: boolean): boolean;
/**
 * Build the multi-document delegation hint message content.
 *
 * @param documentCount - Number of detected documents
 * @param documentNames - Names of detected documents
 * @returns Message content string for injection as HumanMessage
 */
export declare function buildMultiDocHintContent(documentCount: number, documentNames: string[]): string;
/**
 * Build the post-prune context note injected after messages are pruned
 * and summarized. No token numbers — just a contextual signal that
 * earlier conversation was compressed.
 *
 * @param discardedCount - Number of messages that were pruned
 * @param hasSummary - Whether a summary was successfully generated
 * @returns Message content string for injection as SystemMessage, or null if no note needed
 */
export declare function buildPostPruneNote(discardedCount: number, hasSummary: boolean): string | null;
/**
 * Check whether a tool named "task" exists in the agent's tool set.
 *
 * @param tools - Array of tool objects or structured tools
 * @returns Whether the task tool is available
 */
export declare function hasTaskTool(tools: Array<{
    name?: string;
} | unknown> | undefined): boolean;